ML: Multilevel Preconditioning Package. Welcome to the homepages for ML, Sandia’s main multigrid preconditioning package. ML is designed to solve large sparse linear systems of equations arising primarily from elliptic PDE discretizations. ML is used to define and build multigrid solvers and preconditioners, and it contains black-box classes to construct highly-scalable smoothed aggregation preconditioners. ML preconditioners have been used on thousands of processors for a variety of problems, including the incompressible Navier-Stokes equations with heat and mass transfer, linear and nonlinear elasticity equations, the Maxwell equations, semiconductor equations, and more.

References in zbMATH (referenced in 69 articles )

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  1. Ballard, Grey; Siefert, Christopher; Hu, Jonathan: Reducing communication costs for sparse matrix multiplication within algebraic multigrid (2016)
  2. Chidyagwai, Prince; Ladenheim, Scott; Szyld, Daniel B.: Constraint preconditioning for the coupled Stokes-Darcy system (2016)
  3. Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.: Teko: a block preconditioning capability with concrete example applications in Navier-Stokes and MHD (2016)
  4. Gholami, Amir; Malhotra, Dhairya; Sundar, Hari; Biros, George: FFT, FMM, or multigrid? A comparative study of state-of-the-art Poisson solvers for uniform and nonuniform grids in the unit cube (2016)
  5. Hamilton, Steven P.; Evans, Thomas M.: Efficient solution of the simplified $P_N$ equations (2015)
  6. Notay, Yvan; Napov, Artem: A massively parallel solver for discrete Poisson-like problems (2015)
  7. Rhebergen, Sander; Wells, Garth N.; Wathen, Andrew J.; Katz, Richard F.: Three-field block preconditioners for models of coupled magma/mantle dynamics (2015)
  8. Badia, Santiago; Martín, Alberto F.; Principe, Javier: A highly scalable parallel implementation of balancing domain decomposition by constraints (2014)
  9. Bosch, Jessica; Stoll, Martin; Benner, Peter: Fast solution of Cahn-Hilliard variational inequalities using implicit time discretization and finite elements (2014)
  10. Evans, Thomas M.; Mosher, Scott W.; Slattery, Stuart R.; Hamilton, Steven P.: A Monte Carlo synthetic-acceleration method for solving the thermal radiation diffusion equation (2014)
  11. Ganis, Benjamin; Juntunen, Mika; Pencheva, Gergina; Wheeler, Mary F.; Yotov, Ivan: A global Jacobian method for mortar discretizations of nonlinear porous media flows (2014)
  12. Kramer, Richard M.J.; Bochev, Pavel B.; Siefert, Christopher M.; Voth, Thomas E.: Algebraically constrained extended edge element method (\bfeXFEM-AC) for resolution of multi-material cells (2014)
  13. Phillips, Edward G.; Elman, Howard C.; Cyr, Eric C.; Shadid, John N.; Pawlowski, Roger P.: A block preconditioner for an exact penalty formulation for stationary MHD (2014)
  14. Rhebergen, Sander; Wells, Garth N.; Katz, Richard F.; Wathen, Andrew J.: Analysis of block preconditioners for models of coupled magma/mantle dynamics (2014)
  15. Stoll, Martin: One-shot solution of a time-dependent time-periodic PDE-constrained optimization problem (2014)
  16. Bauer, Carl A.; Werner, Gregory R.; Cary, John R.: A fast multigrid-based electromagnetic eigensolver for curved metal boundaries on the Yee mesh (2013)
  17. Benzi, Michele; Wang, Zhen: A parallel implementation of the modified augmented Lagrangian preconditioner for the incompressible Navier-Stokes equations (2013)
  18. Brown, Jed; Smith, Barry; Ahmadia, Aron: Achieving textbook multigrid efficiency for hydrostatic ice sheet flow (2013)
  19. Cyr, Eric C.; Shadid, John N.; Tuminaro, Raymond S.; Pawlowski, Roger P.; Chacón, Luis: A new approximate block factorization preconditioner for two-dimensional incompressible (reduced) resistive MHD (2013)
  20. Howle, Victoria E.; Kirby, Robert C.; Dillon, Geoffrey: Block preconditioners for coupled physics problems (2013)

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